Senior Machine Learning Engineer
Anno.ai
- Location
- US
- Workplace
- Remote
- Employment
- Full Time
- Salary
- —
Posted 2mo ago
The employer’s full description could not be read from their board. This is a summary of the posting — follow the apply link for the original.
Responsibilities
- Design, develop, test, document, deploy, and maintain ML and statistical models
- Operationalize ML models with robust, scalable pipelines
- Translate mission requirements into deployable ML capabilities
- Implement automated CI/CD workflows for ML systems
- Manage ML runtime infrastructure using containerization and orchestration
- Develop monitoring systems for model health and performance
- Ensure ML deployments meet security requirements
- Evaluate and integrate emerging MLOps and inference technologies
Requirements
- Bachelor’s degree in Computer Science, Electrical Engineering, Data Science, or related
- 5+ years of professional experience in software engineering, ML engineering, or MLOps
- Experience operationalizing ML systems at production scale
- Strong proficiency in Python
- Familiarity with at least one deep learning framework (PyTorch, TensorFlow)
- Hands-on experience with MLOps frameworks and workflow tooling (MLflow, Kubeflow, Airflow, DVC, BentoML)
- Experience deploying containerized ML services using Docker
- Experience orchestrating workloads using Kubernetes
- Understanding of CI/CD workflows and DevOps practices applied to ML systems
- Familiarity with monitoring, observability, and logging platforms (Prometheus, Grafana, ELK/EFK)
- Ability to obtain and maintain U.S. Government security clearance
- U.S. citizenship required
- Ability to travel up to 20%
Preferred
- Master’s degree
- Experience deploying models and associated runtimes to Edge devices
- Experience optimizing models for memory and CPU constrained systems
- Prior experience supporting U.S. Department of War programs, cUAS systems, or mission-critical autonomous platforms
- Experience working with diverse or atypical data sources (Audio/Acoustics, RF signals, EO/IR imagery)
- Experience deploying and optimizing ML inference on edge or resource-limited compute systems
- Experience with Explainable/Auditable AI/ML tools and interpretable model design
- Experience with AI Software Development Tools (GitHub CoPilot, Claude)
Skills
- Python
- PyTorch
- TensorFlow
- MLflow
- Kubeflow
- Airflow
- DVC
- BentoML
- Docker
- Kubernetes
- Git
- Prometheus
- Grafana
- ELK
- EFK
- Seldon
- KServe
- GitHub CoPilot
- Claude
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